The third-generation tyrosine kinase inhibitor osimertinib is approved to treat patients with T790M-positive non-small cell lung cancer (NSCLC) who have developed resistance to earlier-generation drugs. Acquired C797S mutation has been reported to mediate osimertinib resistance in some patients. However, the remaining resistance mechanisms are largely unknown. We performed mutation profiling using targeted next-generation sequencing (NGS) for 416 cancer-relevant genes on 93 osimertinib-resistant lung cancer patients' samples, mainly cell-free DNAs (cfDNAs), and matched pretreatment samples of 12 patients. experiments were conducted to functionally study the secondary mutations identified. G796/C797, L792, and L718/G719 mutations were identified in 24.7%, 10.8%, and 9.7% of the cases, respectively, with certain mutations coexisting in one patient with different prevalence. L792 and L718 mutants markedly increased the half inhibitory concentration (IC) of osimertinib , among which the L718Q mutation conferred the greatest resistance to osimertinib, as well as gefitinib resistance when not coexisting with T790M. Further analysis of the 12 matched pretreatment samples confirmed that these mutations were acquired during osimertinib treatment. Alterations in parallel or downstream oncogenes such as , and were also discovered, potentially contributing to the osimertinib-resistance in patients without secondary mutations. We present comprehensive mutation profiles of a large cohort of osimertinib-resistance lung cancer patients using mainly cfDNA. Besides C797 mutations, novel secondary mutations of L718 and L792 residues confer osimertinib resistance, both and , and are of great clinical and pharmaceutical relevance..

Cancer is a disease of complex genetic alterations, and comprehensive genetic diagnosis is beneficial to match each patient to appropriate therapy. However, acquisition of representative tumor samples is invasive and sometimes impossible. Circulating tumor DNA (ctDNA) is a promising tool to use as a non-invasive biomarker for cancer mutation profiling. Here we implemented targeted next generation sequencing (NGS) with a customized gene panel of 382 cancer-relevant genes on 605 ctDNA samples in multiple cancer types. Overall, tumor-specific mutations were identified in 87% of ctDNA samples, with mutation spectra highly concordant with their matched tumor tissues. 71% of patients had at least one clinically-actionable mutation, 76% of which have suggested drugs approved or in clinical trials. In particular, our study reveals a unique mutation spectrum in Chinese lung cancer patients which could be used to guide treatment decisions and monitor drug-resistant mutations. Taken together, our study demonstrated the feasibility of clinically-useful targeted NGS-based ctDNA mutation profiling to guide treatment decisions in cancer.

Purpose: Immune checkpoint inhibitors (ICI) have revolutionized cancer management. However, molecular determinants of response to ICIs remain incompletely understood. Experimental Design: We performed genomic profiling of 78 patients with non-small cell lung cancer (NSCLC) who underwent anti-PD-(L)1 therapies by both whole-exome and targeted next-generation sequencing (a 422-cancer-gene panel) to explore the predictive biomarkers of ICI response. Tumor mutation burden (TMB), and specific somatic mutations and copy-number alterations (CNA) were evaluated for their associations with immunotherapy response. Results: We confirmed that high TMB was associated with improved clinical outcomes, and TMB quantified by gene panel strongly correlated with WES results (Spearman's r ¼ 0.81). Compared with wild-type, patients with FAT1 mutations had higher durable clinical benefit (DCB, 71.4% vs. 22.7%, P ¼ 0.01) and objective response rates (ORR, 57.1% vs. 15.2%, P ¼ 0.02). On the other hand, patients with activating mutations in EGFR/ERBB2 had reduced median progression-free survival (mPFS) compared with others [51.0 vs. 70.5 days, P ¼ 0.0037, HR, 2.47; 95% confidence interval (CI), 1.32-4.62]. In addition, copy-number loss in specific chromosome 3p segments containing the tumorsuppressor ITGA9 and several chemokine receptor pathway genes, were highly predictive of poor clinical outcome (survival rates at 6 months, 0% vs. 31%, P ¼ 0.012, HR, 2.08; 95% CI, 1.09-4.00). Our findings were further validated in two independently published datasets comprising multiple cancer types. Conclusions: We identified novel genomic biomarkers that were predictive of response to anti-PD-(L)1 therapies. Our findings suggest that comprehensive profiling of TMB and the aforementioned molecular markers could result in greater predictive power of response to ICI therapies in NSCLC.

Sustained expression of the oestrogen receptor alpha (ESR1) drives two-thirds of breast cancer and defines the ESR1-positive subtype. ESR1 engages enhancers upon oestrogen stimulation to establish an oncogenic expression program1. Somatic copy number alterations involving the ESR1 gene occur in approximately 1% of ESR1-positive breast cancers2–5, implying that other mechanisms underlie the persistent expression of ESR1. We report the significant enrichment of somatic mutations within the set of regulatory elements (SRE) regulating ESR1 in 7% of ESR1-positive breast cancers. These mutations regulate ESR1 expression by modulating transcription factor binding to the DNA. The SRE includes a recurrently mutated enhancer whose activity is also affected by a functional inherited single nucleotide variant (SNV) rs9383590 that accounts for several breast cancer risk-loci. Our work highlights the importance of considering the combinatorial activity of regulatory elements as a single unit to delineate the impact of noncoding genetic alterations on single genes in cancer.

ObjectiveTo monitor trastuzumab resistance and determine the underlying mechanisms for the limited response rate and rapid emergence of resistance of HER2+ metastatic gastric cancer (mGC).DesignTargeted sequencing of 416 clinically relevant genes was performed in 78 paired plasma and tissue biopsy samples to determine plasma-tissue concordance. Then, we performed longitudinal analyses of 97 serial plasma samples collected from 24 patients who were HER2+  to track the resistance during trastuzumab treatment and validated the identified candidate resistance genes.ResultsThe results from targeted sequencing-based detection of somatic copy number alterations (SCNA) of HER2 gene were highly consistent with fluorescence in situ hybridisation data, and the detected HER2 SCNA was better than plasma carcinoembryonic antigen levels at predicting tumour shrinkage and progression. Furthermore, most patients with innate trastuzumab resistance presented high HER2 SCNA during progression compared with baseline, while HER2 SCNA decreased in patients with acquired resistance. PIK3CA mutations were significantly enriched in patients with innate resistance, and ERBB2/4 genes were the most mutated genes, accounting for trastuzumab resistance in six (35.3%) and five (29.4%) patients in baseline and progression plasma, respectively. Patients with PIK3CA/R1/C3 or ERBB2/4 mutations in the baseline plasma had significantly worse progression-free survival. Additionally, mutations in NF1 contributed to trastuzumab resistance, which was further confirmed through in vitro and in vivo studies, while combined HER2 and MEK/ERK blockade overcame trastuzumab resistance.ConclusionLongitudinal circulating tumour DNA sequencing provides novel insights into gene alterations underlying trastuzumab resistance in HER2+mGC.

Pleural effusion (PE) is commonly observed in advanced lung cancer and was suggested to contain both cell-free tumor DNA and tumor cells. Molecular profiling of PE represents a minimally invasive approach of detecting tumor driver mutations for clinical decision making, especially when tumor tissues are not available. The objective of this study is to investigate the efficacy and precision of detecting gene alterations in PE samples to address the feasibility in clinical use.Methods: Sixty-three metastatic lung cancer patients with (n=30, cohort 1) or without (n=33, cohort 2) matched tumor tissues were enrolled in this study. PE and plasma samples of each patient were collected simultaneously. Supernatant and cell precipitate of PE were processed separately to extract cfDNA (PE-cfDNA) and sediment DNA (sDNA). All samples were subjected to targeted next-generation sequencing (NGS) of 416 cancer-related genes.Results: PE supernatants contain more abundant tumor DNA than PE sediments and plasma samples, suggested by higher mutant allele frequencies (MAF) and elevated mutation detection rate in PE-cfDNA (98.4% vs. 90.5% in PE sDNA vs. 87% in plasma cfDNA). In Cohort 1 with matched tumor tissue, tumor mutational burden (TMB) of PE-cfDNA was similar as tumor tissues (6.4 vs. 5.6), but significantly higher than PE sDNA (median TMB: 3.3) and plasma cfDNA (median TMB: 3.4). Ninety-three percent (27 out of 29) of tissue-determined driver mutations were detected in PE-cfDNA, including alterations in ALK, BRAF, EGFR, ERBB2, KRAS, NF1, PIK3CA, and RET, while only 62% were captured in plasma cfDNA. PE-cfDNA also has the highest detection rate of EGFR driver mutations in the full cohort (71% vs. 68% in PE sDNA vs. 59% in plasma cfDNA). Mutation detection from cytological negative and hemorrhagic PE is challenging. Comparatively, PE-cfDNA demonstrated absolute superiority than PE sDNA in such a scenario, suggesting that it is an independent source of tumor DNA and therefore less influenced by the abundance of tumor cells.Conclusion: Genomic profiling of PE-cfDNA offers an alternative, and potentially more meticulous approach in assessing tumor genomics in advanced lung cancer when tumor tissue is not available. Our data further demonstrate that in hemorrhagic or cytologically negative PE samples, PE-cfDNA has higher mutation detection sensitivity than sDNA and plasma cfDNA, and therefore is a more reliable source for genetic testing.

EGFR exon 20 insertions (EGFR e20ins) account for up to 10% of EGFR mutations in lung cancer; however, tumors with EGFR e20ins had poor response rates to EGFR tyrosine kinase inhibitors (TKIs) including gefitinib, erlotinib, afatinib, and osimertinib, and the heterogeneity of EGFR e20ins further complicates the clinical studies. Here, we retrospectively screened next-generation sequencing (NGS) data from 24 468 lung cancer patients, and a total of 85 unique EGFR e20ins variants were identified in 547 cases (2.24%), with p.A767_V769dup (25.1%) and p.S768_D770dup (17.6%) being the most prevalent ones. Comprehensive genomic profiling revealed that TP53 mutations frequently coexisted with p.H773dup (77.8%, P = 0.0558) and p.A767_V769dup (62.8%, P = 0.0325), while RB1 mutations usually co-occurred with p.H773_V774insAH (33.3%, P = 0.0551), implying that different EGFR e20ins variants might require distinct genomic context for tumorigenesis and/or maintenance. Despite that treatment regimens were highly diverse for EGFR e20ins-positive patients, we observed an overall response rate of 14% and a disease control rate (DCR) of 38.4% in 65 patients who received at least one EGFR TKI. The progression-free survival (PFS) differs significantly in six representative EGFR e20ins variants (P = 0.017), and EGFR p.A763_Y764insF-QEA was associated with better PFS than other EGFR e20ins when treating with various EGFR TKIs. Some EGFR e20ins variants showed at least partial response to first-generation EGFR TKIs, including p.A767_V769dup, p.S768_D770dup, p.N771_H773dup, p.A763_Y764insF-QEA, and p.D770_N771insG. Poziotinib achieved higher DCR for p.S768_D770dup than for p.A767_V769dup, whereas osimertinib showed limited effects for these two insertions when used as the first-line treatment. Overall, our results demonstrated that EGFR e20ins were highly diversified in terms of insertion patterns and co-occurring mutations and these EGFR e20ins variants showed different clinical responses to various EGFR TKIs,

Background For locally advanced rectal cancer (LARC) patients who receive neoadjuvant chemoradiotherapy (nCRT), there are no reliable indicators to accurately predict pathological complete response (pCR) before surgery. For patients with clinical complete response (cCR), a “Watch and Wait” (W&W) approach can be adopted to improve quality of life. However, W&W approach may increase the recurrence risk in patients who are judged to be cCR but have minimal residual disease (MRD). Magnetic resonance imaging (MRI) is a major tool to evaluate response to nCRT; however, its ability to predict pCR needs to be improved. In this prospective cohort study, we explored the value of circulating tumor DNA (ctDNA) in combination with MRI in the prediction of pCR before surgery and investigated the utility of ctDNA in risk stratification and prognostic prediction for patients undergoing nCRT and total mesorectal excision (TME). Methods and findings We recruited 119 Chinese LARC patients (cT3-4/N0-2/M0; median age of 57; 85 males) who were treated with nCRT plus TME at Fudan University Shanghai Cancer Center (China) from February 7, 2016 to October 31, 2017. Plasma samples at baseline, during nCRT, and after surgery were collected. A total of 531 plasma samples were collected and subjected to deep targeted panel sequencing of 422 cancer-related genes. The association among ctDNA status, treatment response, and prognosis was analyzed. The performance of ctDNA alone, MRI alone, and combining ctDNA with MRI was evaluated for their ability to predict pCR/non-pCR. Ranging from complete tumor regression (pathological tumor regression grade 0; pTRG0) to poor regression (pTRG3), the ctDNA clearance rate during nCRT showed a significant decreasing trend (95.7%, 77.8%, 71.1%, and 66.7% in pTRG 0, 1, 2, and 3 groups, respectively, P = 0.008), while the detection rate of acquired mutations in ctDNA showed an increasing trend (3.8%, 8.3%, 19.2%, and 23.1% in pTRG 0, 1, 2, and 3 groups, respectively, P = 0.02). Univariable logistic regression showed that ctDNA clearance was associated with a low probability of non-pCR (odds ratio = 0.11, 95% confidence interval [95% CI] = 0.01 to 0.6, P = 0.04). A risk score predictive model, which incorporated both ctDNA (i.e., features of baseline ctDNA, ctDNA clearance, and acquired mutation status) and MRI tumor regression grade (mrTRG), was developed and demonstrated improved performance in predicting pCR/non-pCR (area under the curve [AUC] = 0.886, 95% CI = 0.810 to 0.962) compared with models derived from only ctDNA (AUC = 0.818, 95% CI = 0.725 to 0.912) or only mrTRG (AUC = 0.729, 95% CI = 0.641 to 0.816). The detection of potential colorectal cancer (CRC) driver genes in ctDNA after nCRT indicated a significantly worse recurrence-free survival (RFS) (hazard ratio [HR] = 9.29, 95% CI = 3.74 to 23.10, P < 0.001). Patients with detectable driver mutations and positive high-risk feature (HR_feature) after surgery had the highest recurrence risk (HR = 90.29, 95% CI = 17.01 to 479.26, P < 0.001). Limitations include relatively small sample size, lack of independent external validation, no serial ctDNA testing after surgery, and a relatively short follow-up period. Conclusions The model combining ctDNA and MRI improved the predictive performance compared with the models derived from individual information, and combining ctDNA with HR_feature can stratify patients with a high risk of recurrence. Therefore, ctDNA can supplement MRI to better predict nCRT response, and it could potentially help patient selection for nonoperative management and guide the treatment strategy for those with different recurrence risks.